code: def test_default_supervised_model(self, mock_handler):
      # create project
      self.run_sql("create database proj")
      df = pd.read_csv(
          "tests/unit/ml_handlers/data/anomaly_detection.csv"
      )
      self.set_handler(mock_handler, name="pg", tables={"df": df})
  
      # create predictor
      self.run_sql(
          """
             create model proj.modelx
             from pg (select * from df)
             predict class
             using
               engine='anomaly_detection',
               type='supervised'
          """
      )
      self.wait_predictor("proj", "modelx")
  
      # run predict
      ret = self.run_sql(
          """
             SELECT p.*
             FROM pg.df as t
             JOIN proj.modelx as p
          """
      )
      assert len(ret) == len(df)
  
      ret = self.run_sql(
          """
             describe model proj.modelx.model
          """
      )
      assert ret["model_name"][0] == "CatBoostClassifier"
  
file_path: mindsdb/tests/unit/ml_handlers/test_anomaly_detection.py
imports: import time
  import pandas
  from unittest.mock import patch
  from mindsdb_sql import parse_sql
  from tests.unit.executor_test_base import BaseExecutorTest
  from mindsdb.integrations.handlers.anomaly_detection_handler.anomaly_detection_handler import choose_model, preprocess_data
label_desc: Use image node_id 3 for calling the TestAnomalyDetectionHandler obj's underlying member method code with example usage: obj.test_default_supervised_model(mock_handler) without return types